Core outcome sets for trials of interventions to prevent and to treat multimorbidity in low- and middle-income countries: the COSMOS study
Notice bibliographique
Résumé
ABSTRACT Introduction The burden of multimorbidity is recognised increasingly in low- and middle-income countries (LMICs), creating a strong emphasis on the need for effective evidence-based interventions. A core outcome set (COS) appropriate for the study of multimorbidity in LMIC contexts does not presently exist. This is required to standardise reporting and contribute to a consistent and cohesive evidence-base to inform policy and practice. We describe the development of two COS for intervention trials aimed at the prevention and treatment of multimorbidity in LMICs. Methods To generate a comprehensive list of relevant prevention and treatment outcomes, we conducted a systematic review and qualitative interviews with people with multimorbidity and their caregivers living in LMICs. We then used a modified two-round Delphi process to identify outcomes most important to four stakeholder groups with representation from 33 countries (people with multimorbidity/caregivers, multimorbidity researchers, healthcare professionals, and policy makers). Consensus meetings were used to reach agreement on the two final COS. Registration: https://www.comet-initiative.org/Studies/Details/1580 . Results The systematic review and qualitative interviews identified 24 outcomes for prevention and 49 for treatment of multimorbidity. An additional 12 prevention, and six treatment outcomes were added from Delphi round one. Delphi round two surveys were completed by 95 of 132 round one participants (72.0%) for prevention and 95 of 133 (71.4%) participants for treatment outcomes. Consensus meetings agreed four outcomes for the prevention COS: (1) Adverse events, (2) Development of new comorbidity, (3) Health risk behaviour, and (4) Quality of life; and four for the treatment COS: (1) Adherence to treatment, (2) Adverse events, (3) Out-of-pocket expenditure, and (4) Quality of life. Conclusion Following established guidelines, we developed two COS for trials of interventions for multimorbidity prevention and treatment, specific to LMIC contexts. We recommend their inclusion in future trials to meaningfully advance the field of multimorbidity research in LMICs. KEY MESSAGES What is already known on this topic? Although a Core Outcome Set (COS) for the study of multimorbidity has been previously developed, it does not include contributions from low- and middle-income countries (LMICs). Given the important differences in disease patterns and healthcare systems between high-income country (HIC) and LMIC contexts, a fit-for-purpose COS for the study of multimorbidity specific to LMICs is urgently needed. What this study adds Following rigorous guidelines and best practice recommendations for developing COS, we have identified four core outcomes for including in trials of interventions for the prevention and four for the treatment of multimorbidity in LMIC settings. The outcomes ‘Adverse events’ and ‘Quality of life (including Health-related quality of life)’ featured in both prevention and treatment COS. In addition, the prevention COS included ‘Development of new comorbidity’ and ‘Health risk behaviour’, whereas the treatment COS included ‘Adherence to treatment’ and ‘Out-of-pocket expenditure’ outcomes. How this study might affect research, practice, or policy The multimorbidity prevention and treatment COS will inform future trials and intervention study designs by helping promote consistency in outcome selection and reporting. COS for multimorbidity interventions that are context-sensitive will likely contribute to reduced research waste, harmonise outcomes to be measured across trials, and advance the field of multimorbidity research in LMIC settings to enhance health outcomes for those living with multimorbidity.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,318 | 0,358 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,010 | 0,016 |
| Bibliométrie | 0,006 | 0,007 |
| Études des sciences et des technologies | 0,002 | 0,004 |
| Communication savante | 0,006 | 0,006 |
| Science ouverte | 0,003 | 0,010 |
| Intégrité de la recherche | 0,004 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; l’étiquette directe de Gemma et le classifieur distillé Codex s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».